Preclinical magnetic resonance imaging (MRI) is a critical component in a co-clinical research pipeline. Importantly, segmentation of tumors in MRI is a necessary step in tumor phenotyping and assessment of response to therapy. However, manual segmentation is time-intensive and suffers from inter- and intra- observer variability and lack of reproducibility. This study aimed to develop an automated pipeline for accurate localization and delineation of TNBC PDX tumors from preclinical T1w and T2w MR images using a deep learning (DL) algorithm and to assess the sensitivity of radiomic features to tumor boundaries. We tested five network architectures including U-Net, dense U-Net, Res-Net, recurrent residual UNet (R2UNet), and dense R2U-Net (D-R2UNet), which were compared against manual delineation by experts. To mitigate bias among multiple experts, the simultaneous truth and performance level estimation (STAPLE) algorithm was applied to create consensus maps. Performance metrics (F1-Score, recall, precision, and AUC) were used to assess the performance of the networks. Multi-contrast D-R2UNet performed best with F1-score = 0.948; however, all networks scored within 1–3% of each other. Radiomic features extracted from D-R2UNet were highly corelated to STAPLE-derived features with 67.13% of T1w and 53.15% of T2w exhibiting correlation ρ ≥ 0.9 (p ≤ 0.05). D-R2UNet-extracted features exhibited better reproducibility relative to STAPLE with 86.71% of T1w and 69.93% of T2w features found to be highly reproducible (CCC ≥ 0.9, p ≤ 0.05). Finally, 39.16% T1w and 13.9% T2w features were identified as insensitive to tumor boundary perturbations (Spearman correlation (−0.4 ≤ ρ ≤ 0.4). We developed a highly reproducible DL algorithm to circumvent manual segmentation of T1w and T2w MR images and identified sensitivity of radiomic features to tumor boundaries.

Carcinoma of oral cavity have a high risk of recurrence after initial treatment with surgery, radiotherapy, surgery with adjuvant radiotherapy, or radio-chemotherapy.The present study investigated the changes in expression, activity and regulation of matrix metalloproteinases (MMP) -2 and -9 in oral squamous cell carcinoma (OSCC) which might help to ascertain the invasive potential of the tumor .Tumor tissues and adjacent normal tissues of OSCC patients [N,37; either sex; 20-70 yrs] were subjected to clinico-pathology, histopathology and TNM grading. The enzyme activity and associated signalling was observed with gelatin zymography, immunohistochemistry, ELISA, western blot and semi quantitative reverse transcriptase PCR.OSCC tissues were observed with elevated MMP-9 activity, enhanced expression of fibronectin (FN), phosphorylated focal adhesion kinase (FAK Try 397), phosphatidyl inositol 3-kinase (PI3K), protein kinase B (AKT) and reduced expression of tissue inhibitor of metalloproteinase-1(TIMP-1) than the control tissues.OSCC patients elicited a predominance of MMP-9 activity via up regulated FAK/PI3K/AKT pathway. A routine MMP-9 analysis may ascertain the invasiveness of the tumor and therefore may be professed as a suitable biomarker for metastatic potential of oral cancer. Key words: oral squamous cell carcinoma, MMP-9, zymography, eastern IndiaIn India, oral cancer forms a large group of malignancy representing 30-40% of all cancers [1]. By the year 2020 cancers of the mouth (64,525; 29.5%), tongue (38,052; 17.4%) and larynx (33,855,15.5%) will be the major sites of oral cancer [2].The frequency of oral malignancy varies between Indian states which might be due to regional differences in disease-specific risk factors [3]. The pattern of cancer incidence in rural West Bengal showed that the oral cavity, pharynx, larynx contributed to more than half of the cancers in men and about a quarter in women. Indigenous habits of chewing and smoking seemed to be primarily responsible for their high incidence [4].Oral squamous cell carcinoma (OSCC) is one of the deadliest forms of oral malignancy which is associated with high morbidity and mortality, resulting from local, regional and distant metastasis [5]. This creates a great concern for scientists and prioritizes the search for suitable biomarker of oral cancer.Matrix metalloproteinases (MMPs) are the principal mediators for the degradation of extracellular matrix (ECM) components which take place during the invasion and metastasis [6,7]. MMPs are zinc dependent family of endopeptidases and the gelatinases, MMP-2 (Gelatinase A, 72 KDa) and MMP-9 (Gelatinase B 92 KDa), are the master molecules for the malignant phenotype because of their unique property to degrade type IV collagen, a major component of the basement membrane [8].The orchestra of signaling molecules associated with MMP regulation is highly complicated. In areas with basement membrane defects the invading carcinoma cells may come in contact with the abundant stromal fibronectin (FN) matrix. The 12...

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